Electric Power Transmission Network Research Articles

Convex Relaxations of Maximal Load Delivery for Multi-Contingency Analysis of Joint Electric Power and Natural Gas Transmission Networks

Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically operated independently, coordination of these systems during severe disruptions can allow for targeted delivery to lifeline services, including gas delivery for residential heating and power delivery for critical facilities. To address the challenge of estimating maximum joint network capacities under such disruptions, we consider the task of determining feasible steady-state operating points for severely damaged systems while ensuring the maximal delivery of gas and power loads simultaneously, represented mathematically as the nonconvex joint Maximal Load Delivery (MLD) problem. To increase its tractability, we present a mixed-integer convex relaxation of the MLD problem. Then, to demonstrate the relaxation’s effectiveness in determining bounds on network capacities, exact and relaxed MLD formulations are compared across various multi-contingency scenarios on nine joint networks ranging in size from 25 to 1191 nodes. The relaxation-based methodology is observed to accurately and efficiently estimate the impacts of severe joint network disruptions, often converging to the relaxed MLD problem’s globally optimal solution within ten seconds.

Transmission Line Fault Classification Based on the Combination of Scaled Wavelet Scalograms and CNNs Using a One-Side Sensor for Data Collection.

This research focuses on leveraging wavelet transform for fault classification within electrical power transmission networks. This study meticulously examines the influence of various parameters, such as fault resistance, fault inception angle, fault location, and other essential components, on the accuracy of fault classification. We endeavor to explore the interplay between classification accuracy and the input data while assessing the efficacy of combining wavelet analysis with deep learning methodologies. The data, sourced from network recorders, including phase currents and voltages, undergo a scaled continuous wavelet transform (S-CWT) to generate scalogram images. These images are subsequently utilized as inputs for pretrained deep learning models. The experiments encompass various fault scenarios, spanning distinct fault types, locations, times, and resistance values. A remarkable feature of the proposed work is the attainment of 100% classification accuracy, obviating the need for additional algorithmic enhancements. The foundation of this achievement is the deliberate selection of the right input. The decision to employ an identical number of samples as the number of scales for the CWT emerges as a pivotal factor. This approach underpins the high accuracy and renders supplementary algorithms superfluous. Furthermore, this research underscores the versatility of this approach, showcasing its effectiveness across diverse networks and scenarios. Wavelet transform, after rigorous experimentation, emerges as a reliable tool for capturing transient fault characteristics with an optimal balance between time and frequency resolutions.

Vulnerability Analysis of Power Transmission Grids Subject to Cascading Failures

Cascading failures are a major threat to interconnected systems, such as electrical power transmission networks. Typically, approaches proposed for devising optimized control strategies are demonstrated with reference to a few test systems of reference (IEEE systems). However, this limits the robustness of the proposed strategies with respect to different power grid structures. Recently, this issue has been addressed by considering synthetic networks randomly generated for mimicking power transmission grids’ characteristics. These networks can be used for investigating the vulnerability of power networks to cascading failures. In this work, we propose to apply a recent algorithm for sampling random power grid topologies with realistic electrical parameters and further extend it to the random allocation of generation and load. Integration with a realistic cascade simulation tool, then, allows us to perform thorough statistical analyses of power grids with respect to their cascading failure behavior, thus offering a powerful tool for identifying the strengths and weaknesses of different grid classes. New metrics for ranking the control and mitigation effort requirements of individual cascade scenarios and/or of grid configurations are defined and computed. Finally, genetic algorithms are used to identify strategies to improve the robustness of existing power networks.

LEGAL OVERVIEW OF COMPENSATION FOR LAND IN THE DEVELOPMENT OF PT. PLN'S SUTET TOWER NETWORK IN THE TAKTAKAN DISTRICT OF SERANG CITY, BANTEN PROVINCE

The implementation of land compensation to the community for the construction of the Extra High Voltage Transmission Network (SUTET) by PLN falls under the Ministry of Energy and Mineral Resources (ESDM). The Ministry of Energy and Mineral Resources released Ministerial Regulation (Permen) ESDM number 13 of 2021 regarding Free Space and Minimum Clearance Distance for Electric Power Transmission Network and Compensation for Land, Buildings, and/or Plants Located in the Free Space of Electric Power Transmission Network. This regulation was enacted by Minister of ESDM Arifin Tasrif on June 17, 2021, and took effect upon its promulgation on June 17, 2021. With this regulation, the rights of the community whose land is traversed by the transmission will receive compensation. However, the regulation does not comprehensively address the impact of the development and compensation for the transmission lines of 500 kV or 150 kV, leading to injustice and legal uncertainty. PLN's responsibility for the land value of the community affected by the construction of the SUTET transmission network is limited. In providing compensation to the community whose land is traversed by the Extra High Voltage Transmission Line (SUTET), PT PLN follows existing regulations. PLN refers to Ministerial Regulation No. 01.P/47/MPE/1992 on SUTET Free Space and SUTET for Electricity Distribution Article 5 paragraph (3) concerning land for establishing support structures, including buildings and plants on that land, which must be cleared and compensated.

Hybrid DGA Method for Power Transformer Faults Diagnosis Based on Evolutionary k-Means Clustering and Dissolved Gas Subsets Analysis

Considered as the heart of electrical power transmission and distribution networks, power transformers are essential part of the electricity transmission grid. Among the condition monitoring and fault diagnosis tools for these machines, dissolved gas analysis (DGA) has proven its effectiveness in their early detection and classification of faults. Up to date, many methods have been proposed in the literature for the interpretation of DGA data, classified into traditional and intelligent methods. This paper proposes a two-steps hybrid method, which uses the strengths of both methods. The approach uses the evolutionary k-means clustering algorithm based on the genetic algorithm for subset formation and subset analysis by human expertise. In the diagnostic procedure, to determine the condition of a sample, the subset to which it belongs is first identified and then the corresponding diagnostic sub-model is applied. The proposed method has been implemented with 595 DGA data, tested on 254 DGA data and validated on the International Electrotechnical Commission (IEC) TC10 database. Their performances were evaluated and compared with existing traditional, intelligent and hybrid methods. From the results obtained with the IEC TC10 database, the newly proposed approach depicts the best overall diagnosis accuracies. Indeed, the best performance is achieved with the proposed method compared to other models in the literature, with diagnostic accuracy of 98.29% compared to 88.89% of the Gouda triangle method, to 88.03% of the Hyosun Corporation gas ratio method or to 86.32% of the three ratios technique.

Time-synchronized carbon flow metering scheme for electric power transmission, transformation, and distribution networks

Faced with the pressure of energy conservation and emission reduction, the power industry is urgently requires low-carbon transformation. The carbon flow calculation theory redistributes the actual carbon generated by the power plant to the branch and loads customers with the power flow. This paper first introduces the theory of carbon flow calculation and the carbon metrics corresponding to the electricity metrics. Second, a time-synchronous technology is introduced for the carbon flow calculation of transmission, transformation, and distribution networks, and a time-synchronous-based carbon metering system is conceived. The impact of time deviation on carbon metering is elucidated through simulation experiments of IEEE14 standard nodes, and finally, relevant suggestions are made for future research ideas and technical routes.

Analisis Perbaikan Sistem Pentanahan Tower 70 kV pada Transmisi Wlingi - Blitar

70 KV High Voltage Air Line (in Indonesian known as SUTT) is defined as part of an electric power transmission network that islikely to be struck by lightning. This condition may lead to back flashover (BFO) phenomenon if the grounding value in the transmission is found to be high (>5 Ohms) and may also generate equipment failure. This research was intended to analyze the grounding improvement in tower T17, so that traveling-wave voltages may not result in failure of the main equipment at the substation, specifically the transformer. The value of the traveling wave at the substation was measured through simulation by means of the ATP Draw application in tower T17 to the substation. The grounding value may be reduced by increasing and widening the distance between the electrodes. The value obtained by modeling 4 electrodes with a distance of 0.5 meter was amounted to 1.73 Ohms. Furthermore, modeling 3 electrodes with a distance of 1 meter had successfully generated a value of 1.06 Ohm, and a value of 1.67 Ohm was also successfully obtained through modeling 2 electrodes with a distance of 2 meters. The ground resistance with a value of 67.05 Ohms that has not been repaired will lead to back flashover (BFO) caused by lightning strikes. However, this may be reduced properly with a lightning arrester which is capable of cutting the overvoltage at the substation, so that the voltage entering the transformer is below the BIL (Basic Insulation Level) value.

Experimental Validation of a Mitigation Method of Ferranti Effect in Transmission Line

Electric power transmission networks should be operated in efficient, safe, and reliable conditions. To improve the stability and transfer capability of power transmission, it is necessary to mitigate the Ferranti effect. This paper investigates the impact of increasing the length of the transmission line on its receiving end voltage under no-load conditions. A variable shunt reactor compensation for transmission lines is used to control the voltage level at different lengths of the transmission line. The proposed method demonstrates that the value of the shunt reactor required to maintain the receiving end voltage can be estimated. Moreover, the system is modeled using the PowerWorld simulator, and the effectiveness of the proposed model has been verified by experimental results. The experimental results demonstrate the efficiency of the proposed methodology and match the simulation results, which are then validated by simulating the WSCC 9-bus and IEEE 30-bus test systems.

An Efficient and Reliable Electric Power Transmission Network Topology Processing

An Efficient and Reliable Electric Power Transmission Network Topology Processing

Fast Recovery Studies on Thermal Window based Dielectric for HTS Cable

High Temperature Superconducting (HTS) cables have remarkable electric power transmission characteristics compared to conventional power cables. Thus, HTS cables are suitable for the sustainable electrical grids of the future. Electric faults of various origins and durations are inevitable in a commercial electric power transmission network. The integration of HTS cables to these networks requires reliable cable operation under fault conditions. However, it was found that HTS cables require a long recovery interval after the fault and subsequent quench. It is primarily attributed to the high thermal resistance of the cable dielectric layer. An innovative dielectric design is proposed in this article to improve the thermal performance of HTS cables and the results are compared with that of a conventional HTS cable. Transient thermal analysis was carried out to determine the recovery interval and the electric insulation characteristics were studied using an electrostatic analysis. Both studies were performed using Finite Element Analysis (FEA). It was found that a reduction in the recovery interval is possible without deterioration in the electric insulation level.

Geomagnetically Induced Current Modeling in New Zealand: Extreme Storm Analysis Using Multiple Disturbance Scenarios and Industry Provided Hazard Magnitudes

AbstractGeomagnetically induced currents (GICs) are induced in electrical power transmission networks during geomagnetic disturbances. Understanding the magnitude and duration of the GIC expected during worst‐case extreme storm scenarios is vital to estimate potential damages and disruptions to power networks. In this study we utilize the magnetic field waveforms measured during three large geomagnetic storms and scale them to expected worst case extreme storm magnitudes. Multiple methods are used to simulate the varying magnitude of the magnetic field across the different latitudes of New Zealand. Modeled GIC is produced for nine extreme storm scenarios, each covering 1–1.5 days in duration. Our industry partners, Transpower New Zealand Ltd provided GIC magnitude and duration levels which represent a risk to their transformers. Using these thresholds various extreme storm scenarios predict between 44 and 115 New Zealand transformers (13%–35%) are at risk of damaging levels of GIC. The transformers at risk are largely independent of the extreme storm time‐variations, but depend more on the latitude variation scenario. We show that these at‐risk transformers are not localized to any specific region of New Zealand but extend across all regions and include most of the major population centers. A peak mean absolute GIC over a 60‐min window of 920–2,210 A and an instantaneous 1‐min time resolution maximum GIC of 1,590–4,920 A occurs for a worst‐case extreme storm scenario. We believe this is one of the first studies to combine a reasonable worst‐case extreme geomagnetic storm with validated GIC modeling and industry‐provided GIC risk thresholds.

Uncertainty Assessment of Dynamic Thermal Line Rating for Operational Use at Transmission System Operators

Transmission system operators (TSOs) in recent years have faced challenges in order to ensure maximum transmission capacity of the system to satisfy market needs, while maintaining operational safety and permissible impact on the environment. A great help in the decision-making process was introduced with the Dynamic Thermal Rating (DTR) - an instrument to monitor and predict the maximal allowed ampacity of the power grid based on weather measurements and forecast. However, the introduction of DTR raises a number of questions related to the accuracy and uncertainty of the results of thermal assessment and the level of acceptable risk and its management. In this paper, we present a solution for estimating DTR uncertainty, appropriate for operational use at TSOs. With the help of conductor surface temperature measurements, weather measurements and predicted weather data, we also estimate the error of the weather forecast and the DTR itself. Following the results of the data analyses, we build an operative solution for estimating the ampacity uncertainty based on Monte Carlo random simulations and integrate it into the operational environment of ELES - the operator of the Slovenian electric power transmission network.

Improved Randomized Flow Model for 330kV Electric Power Transmission Network

Improved Randomized Flow Model for 330kV Electric Power Transmission Network

Use of the Magnetotelluric Method in Brazil and Future Challenges

The magnetotelluric (MT) method is based on measurements of natural electric and magnetic fields at the Earth’s surface to probe the subsurface electrical resistivity structure. A summary of the use of the method in Brazil is presented, with emphasis on the initial theoretical and experimental developments for its implementation in the country. The expansion of the method in recent years is related both to academic studies on the tectonic evolution of geological provinces and to contracted surveys mainly restricted to support oil exploration. Two major challenges are proposed to increase the contribution of the method in the next years. One is the planning and installation of a large experimental program to obtain long-period data from stations installed in a 3D grid. It can contribute to improve the knowledge of the tectonic evolution of the Brazilian shield and also to locate new areas with potential for exploration of mineral resources. Coupled with this expansion of field measurements, another challenge is the need to formulate new data processing techniques. The main objective will be to minimize the effects of coherent and intermittent EM noise related to the installation in the country of electric power transmission networks using high voltage direct currents (HVDC).

An optimum budget‐based development in maintenance for electric power transmission networks

On the topic of power systems, the most critical assignment would be providing facilities to make electricity available at the lowest price with a fulfilled level of reliability for all consumers. Today, power transmission reliability has received more concentration due to the increasing essence of providing high-quality energy to customers and operating competitive conditions in electricity markets. In this regard, this paper scrutinizes the reliability-centred maintenance (RCM) issue in terms of considering two optimal maintenance strategies for transmission assets to decrease their forced outage rate (FOR). This techno-economic budget-based maintenance is a probabilistic approach to help asset managers and experts in the decision-making process: to determine between maintenance strategies with associated costs and provide the most economical resource allocation for these elements, which leads to an improvement in the reliability of the whole network. Decreasing the average probability of Energy Not-Supplied (ENS), the simulation determined the proper maintenance strategy for transmission components. After that, the repercussions of the fallen ENS will be analyzed in total maintenance cost (MC), operation cost (OC), and the system's total cost (TC). Also, the IEEE 24-bus reliability test system is considered as a case study demonstrating the proposed technique's practicality.

Deep learning for component fault detection in electricity transmission lines

Component fault detection and inventory are one of the most significant bottlenecks facing the electricity transmission and distribution utility establishments especially in developing countries for delivery of efficient services to the customers and to ensure proper asset audit and management for network optimization and load forecasting. For lack of technology and data, insecurity, the complexity associated with traditional methods, untimeliness, and general human cost, electricity assets monitoring, and management have remained a big problem in many developing countries. In view of this, we explored the use of oblique UAV imagery with high spatial resolution and fine-tuned deep Convolutional Neural Networks (CNNs) for automatic faulty component inspection and inventory in an Electric power transmission network (EPTN). This study investigated the capability of the Single Shot Multibox Detector (SSD), a one-stage object detection model on the electric transmission power line imagery to localize, detect and classify faults. Our proposed neural network model is a CNN based on a multiscale layer feature pyramid network (FPN) using aerial image patches and ground truth to localise and detect faults through a one-phase procedure. The SSD Rest50 architecture variation performed the best with a mean Average Precision (mAP) of 89.61%. All the developed SSD-based models achieve a high precision rate and low recall rate in detecting faulty components, thus achieving acceptable balance levels of F1-score and representation. We have established in this paper that combined use of UAV imagery and computer vision presents a low-cost method for easy and timely electricity asset inventory, especially in developing countries. This study also provides the guide to various considerations when adopting this technology in terms of the choice of deep learning architecture, adequate training samples over multiple fault characteristics, effects of data augmentation, and balancing of intra-class heterogeneity.

TOPSIS-Based Algorithm for Resilience Indices Construction and the Evaluation of an Electrical Power Transmission Network

In the context of energy transformation, new energy technologies are developing rapidly, the penetration rate of new energy is increasing, and the energy structure tends to be low-carbon, which leads to the asymmetry between traditional energy and new energy. At present, the smart power grid can be conceived as a complex cyber-physical system, and its resilience assessment in the face of extreme disasters needs more holistic consideration. Therefore, considering the impact of massive access to new energy on the resilience of the power grid main network, the resilience evaluation index system of the power grid main network under the background of the energy transition is established. It is proposed to use the priority comparison method and CRITIC (Criteria Importance Through Intercriteria Correlation) to determine the subjective weight and subjective and objective weight of the index, respectively, and combine the influence of the two weights to obtain the comprehensive weight. Then, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is used to evaluate the regional power grid restoring force. The results of an example show that the proposed method can effectively evaluate the resilience level of the power grid under the background of the energy transition, which has a certain guiding significance for improving the power grid’s resilience under the environment of energy transformation.

Comprehensive Review of Community Seismic Resilience: Concept, Frameworks, and Case Studies

Seismic resilience is a concept to evaluate the postearthquake functionality of structures that significantly play a critical role in postearthquake rescue and recovery. Indeed, the community is made up of more than just buildings; it is also made up of other subsystems such as hospital and school facilities as well as roads, drainage systems, sewer systems, and electrical power transmission networks. In recent years, the concept of community resilience as a tool for disaster risk management has attracted substantial attention from all parties, such as governments, designers, decision-makers, and stakeholders. Community resilience can be assessed more effectively by using a multi-disciplinary approach that takes into account the community’s uncertainties, as opposed to a single-criteria approach. The global community resilience model must be long-term validated and dependent on the most vulnerable and low-resilience portions of the community, according to a prior study. According to the review of the seismic resiliency studies performed in the recent decades, the frameworks for the quantification assessment of the community resilience are explained. Moreover, several case studies for community resilience and the application of different subsystems are reviewed and elaborated in this paper. Based on these resilience studies, the main challenges on the effectiveness of the resilience assessment are the availability and accessibility of the data, the financial resources, and the cooperation from all the parties.

Detection and Analysis of Inter-Area Oscillations Through a Dynamic-Order DMD Approach

The paper deals with a novel method for detecting and analyzing inter-area oscillations on electric power transmission networks. The method starts from the modal analysis performed by the Dynamic Mode Decomposition algorithm, which is able to exploit the synchronized acquisitions of various measurement instruments to detect the mode of a dynamic system. Compared with the classical algorithm, the proposed method presents a fundamental improvement, which ensures its reliability even without having prior information on the type of input signal. In particular, the order of the DMD, i.e. the number of modes characterizing the acquired signal, is dynamically updated according to its energy content. The method has been tested with simulated signals, considering both single-oscillation signals and two-oscillation signals, varying the amplitude, frequency and damping of the oscillatory components. In this way, the improvement with respect to the classical DMD was highlighted and the performance in terms of deviation between the estimated and nominal parameters was evaluated. Furthermore, the assessment on real life acquired signals has been performed; the results confirmed the reliability and accuracy of the measurement method, even in the presence of noisy signals and ambient data.

Simple Approximation of the Magnetic Induction Inside High Voltage Overhead Transmission Lines

With the development of electrical power transmission networks, are resulted the increase and continuous consumption of various power production sources, this is what requires the large quantities of energy construction. The increased demand in electric power employment has generated an raised of operating voltage for transmission lines (HV and VHV). The high voltage overhead transmission lines create electric and magnetic fields, and therefore have elevated serious concern questions about their possible potential effects in human body and environmental great associated with the resulting higher levels of electromagnetic fields strength around these power lines. The accurate evaluation of extremely low frequency electromagnetic fields influences produced by the high voltage overhead power lines on human health and the environment are well very known and analysed in several research works and simulation study projects. In this paper we precise examine and present a methodology for plot the lateral profile of magnetic field distribution in close a three-phase overhead transmission line in single circuit flat horizontal configuration at height 1m above the ground level, In order show the essentials factors affecting in the magnetic fields intensity under and in the vicinity of high voltage overhead transmission line in any point of space surface and ground plane, the analytique calculation results of the lateral profile of magnetic flux density behaviour are obtained by program MATLAB software, which makes it possible better analyser and easy represent the transverse profile of the magnetic field around electric power transmission lines, the numerique simulation results are based in image method and the superposition theorem.